Skip to main content

1 Colour - HDRI

Develop Build Status Coverage Status Code Grade Package Version

A Python package implementing various HDRI processing algorithms.

It is open source and freely available under the BSD-3-Clause terms.

https://raw.githubusercontent.com/colour-science/colour-hdri/master/docs/_static/Radiance_001.png

1.1 Features

The following features are available:

  • HDRI Generation

  • Debevec (1997) Camera Response Function Computation

  • Grossberg (2003) Histogram Based Image Sampling

  • Variance Minimization Light Probe Sampling

  • Global Tonemapping Operators

  • Adobe DNG SDK Colour Processing

  • Absolute Luminance Calibration

  • Digital Still Camera (DSC) Exposure Model

  • Raw Processing Helpers

  • Vignette Characterisation & Correction

1.1.1 Examples

Various usage examples are available from the examples directory.

1.2 User Guide

1.2.1 Installation

Because of their size, the resources dependencies needed to run the various examples and unit tests are not provided within the Pypi package. They are separately available as Git Submodules when cloning the repository.

1.2.1.1 Primary Dependencies

Colour - HDRI requires various dependencies in order to run:

1.2.1.2 Optional Features Dependencies

1.2.1.3 Pypi

Once the dependencies are satisfied, Colour - HDRI can be installed from the Python Package Index by issuing this command in a shell:

pip install --user colour-hdri

The optional features dependencies are installed as follows:

pip install --user 'colour-hdri[optional]'

The figures plotting dependencies are installed as follows:

pip install --user 'colour-hdri[plotting]'

The overall development dependencies are installed as follows:

pip install --user 'colour-hdri[development]'

1.2.2 Contributing

If you would like to contribute to Colour - HDRI, please refer to the following Contributing guide for Colour.

1.2.3 Bibliography

The bibliography is available in the repository in BibTeX format.

1.3 API Reference

The main technical reference for Colour - HDRI is the API Reference.

1.4 See Also

1.4.1 Publications

Advanced High Dynamic Range Imaging: Theory and Practice was used as a reference for some of the algorithms of Colour - HDRI.

1.4.2 Software

C/C++

Piccante was used to verify the Grossberg (2003) Histogram Based Image Sampling.

Matlab

1.5 Code of Conduct

The Code of Conduct, adapted from the Contributor Covenant 1.4, is available on the Code of Conduct page.

1.6 Contact & Social

The Colour Developers can be reached via different means:

1.7 About

Colour - HDRI by Colour Developers
Copyright 2015 Colour Developers – colour-developers@colour-science.org
This software is released under terms of BSD-3-Clause: https://opensource.org/licenses/BSD-3-Clause

Metadata

Release files for colour-hdri 0.2.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for colour-hdri 0.2.3
File Size Uploaded
colour_hdri-0.2.3.tar.gz 9.3 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for colour-hdri 0.2.3
File Interpreter ABI Platform
colour_hdri-0.2.3-py3-none-any.whl Python 3 none any Details

Total release size: 18.6 MB

Release files / colour_hdri-0.2.3.tar.gz

Download URL colour_hdri-0.2.3.tar.gz
Size 9.3 MB
Tags Source
SHA-256 checksum
How to use checksums
290fd707cc6a693384784d31530ade9f15e8542738edc73e9682e573b11a29db
BLAKE2b-256 checksum
How to use checksums
04bb9639470d4be21a89ed7a563bdf0c9f514289a9ab32731add3775473caa2e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.12.0

Release files / colour_hdri-0.2.3-py3-none-any.whl

Download URL colour_hdri-0.2.3-py3-none-any.whl
Size 9.3 MB
Tags Python 3
SHA-256 checksum
How to use checksums
523bda3582dcc1b787cd7852ffb90ed5e1dc9dbe8df5d00da112af53d5302add
BLAKE2b-256 checksum
How to use checksums
95eb37ad98f4ecb461f7f37611dcc0a11886536a97e3e5f1a53bea421e3f0268
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.12.0

Release history Release notifications | RSS feed

0.2.6

2 release files

0.2.5

2 release files

0.2.4

1 release file

This release

0.2.3 This release

2 release files

0.2.2

2 release files

0.2.1

2 release files

0.2.0

2 release files

0.1.8

2 release files

0.1.7

2 release files

0.1.6

2 release files

0.1.5

2 release files

0.1.4

2 release files

0.1.3

2 release files

0.1.2

2 release files

0.1.1

3 release files

0.1.0

3 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page